System and method for improved computer drug design

Abstract

A system and method for computer-aided drug design employs adaptive sampling and iterative fitting of multi-atomic subunits. The iterative fitting is performed by successive perturbation of the location of the multi-atomic subunits in directions that reduces potential energy.

Description

PRIORITY[0001]This utility patent application claims priority from U.S. Provisional Patent Application No. 60 / 602,955, filed Aug. 19, 2004, and from U.S. Utility patent application Ser. No. 10 / 288,851, the entire specifications of which are hereby incorporated herein.BACKGROUND OF THE INVENTION[0002]Discovery and development of drugs is a lengthy, expensive, and often unsuccessful process. Typically, it takes 12 to 16 years, and more than $500 million from the original concept to the market introduction of a new drug. Numerous software packages have been developed to assist in the development of new drugs. Unfortunately, all of these programs must make tradeoffs between completeness of their searching functions and the speed of their computations. In other words, drug design software that includes more efficient computational methods has a better chance of identifying new, useful drugs.[0003]As is known by those skilled in the art, the vast majority of drugs are small molecules desi...

AI Technical Summary

Benefits of technology

"The patent describes a system and method for computer-aided drug design that use adaptive sampling and rapid minimization techniques to optimize the structure of drug molecules. The system can divide a ligand into smaller subunits and determine force vectors to minimize potential energy. The method also includes steps to determine the optimal six-dimensional coordinates for units using RMS fitting. The technical effects of this patent include improved efficiency and accuracy in drug design, reducing the time and cost of the process."

Problems solved by technology

Calculating derivatives for all the energy terms and locating minima numerically is CPU intensive in its own right.

As such, even the fastest of commercially available minimizers currently requires several minutes to relax a typical ligand-receptor structure.

This nullifies any computational advantage gained from employing a rough conformational search.

For most real-time applications, including docking, automated ligand refinement, and virtual screening, this timeframe is impractical.

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